1. Field of the Invention
The present invention relates to a pathological tissue image capturing system, a pathological tissue image capturing method, and a pathological tissue image capturing program for selecting a range in which to capture an enlarged image from a pathological tissue image and capturing an enlarged pathological tissue image in the selected range.
2. Description of the Related Art
In recent years, the clinical practice has been finding advanced diagnostic imaging devices such as X-ray, CT (Computed Tomography), and MRI (Magnetic Resonance Imaging) devices which are capable of detecting small foreign matter in the patient's body. However, the diagnostic imaging devices produce only positional information of the detected foreign matter in the patient's body, and are unable to identify the property of the foreign matter.
It has been the customary practice for a pathologist to carry out a microscopic observation of a tissue sample that is obtained from the foreign matter detected by the diagnostic imaging device and diagnose the tissue sample to see if the property of the detected foreign matter is benign or malignant based on the experience (pathological issue diagnosis).
In particular, a pathologist performs a pathological issue diagnosis of a cancer as follows:
The pathologist dehydrates a tissue sample obtained from the foreign matter in order to secure the tissue sample in position, and then produces tissue paraffin blocks from the tissue sample.
Then, the pathologist cuts off a slice having a thickness in the range from 4 to 8 micrometers from a tissue paraffin block, and places the slice on a glass slide, preparing a pathological tissue slide.
Then, the pathologist removes the paraffin from the tissue sample on the pathological tissue slide, and dyes the tissue sample with hematoxylin and eosin (HE dyeing). According to the HE dyeing, the cell nuclei included in the tissue sample are dyed in bluish purple, and the other cell cytoplasm, fibers, and blood red cells are dyed in rose pink.
Thereafter, the pathologist observes the HE-dyed tissue sample with a microscope, and performs a pathological issue diagnosis of the tissue sample based on the morphological information produced from the results of the observation.
At this time, the pathologist observes the tissue sample on the pathological tissue slide through a low-magnification objective lens, observes changes in the pattern of the tissue sample, and guesses a region which is suspected of a cancer from the results of the observations. The changes in the pattern of the tissue sample include changes in the density of tissues and cell nuclei and changes in the pattern of cell nuclei.
Thereafter, the pathologist observes the suspected region at an enlarged scale through a high-magnification objective lens, observes changes in the sizes and shapes of the cell nuclei of the tissue sample, and determines the property of the foreign matter from which the tissue sample has been obtained.
In recent years, it has become more popular for the pathologist to capture a pathological tissue image of a pathological tissue slide and performs a pathological tissue diagnosis based on the captured pathological tissue image.
Since a pathological tissue image of a pathological tissue slide in a microscopic field of vision is captured, it can easily be compared with pathological tissue images captured in the past and typical pathological tissue images of pathological tissues inflicted with diseases. Consequently, the pathologist can perform an accurate pathological tissue diagnosis.
There has recently been developed a pathological tissue diagnosis assisting system for assisting the pathologist in making a pathological tissue diagnosis by analyzing a captured pathological tissue image of a tissue sample and performing a basic pathological tissue diagnosis based on the morphological information of the tissue sample which is produced from the pathological tissue image. In the basic pathological tissue diagnosis, the pathological tissue diagnosis assisting system determines a diagnostic category to which the tissue sample belongs and the degree of malignancy of cancer cells contained in the tissue sample. JP-A No. 2006-153742 discloses, as an example of such a pathological tissue diagnosis assisting system, a technology for determining quantitative representations of features of a pathological tissue image and calculating the degrees of conformance of the quantitative representations with diagnostic categories based on pathological tissue features to display the name of a diagnostic category which has a high degree of conformance with the quantitative representations.
Pathological tissue images for use in pathological tissue diagnoses are generally captured by a CCD (Charge-Coupled Device) camera mounted on a microscope.
In the past, it was necessary to develop captured pathological tissue images into photographs. Recently, systems have been developed to allow users to confirm captured pathological tissue images on display monitors. As the time spent in the past to develop captured pathological tissue images into photographs is no longer required, the total period of time consumed by pathological tissue diagnoses is now shortened.
Captured pathological tissue images can be saved as electronic information. Therefore, captured pathological tissue images can be compared with pathological tissue images captured in the past and can also be processed with ease. It is thus possible to perform a quick pathological tissue diagnosis based on the captured pathological tissue images.
There have been proposed a variety of pathological tissue image capturing systems for capturing pathological tissue images and outputting the captured pathological tissue images to display monitors. The proposed pathological tissue image capturing systems include a technology for assisting the pathologist in making a pathological tissue diagnosis by processing captured pathological tissue images.
JP-A No. 11-344676 discloses, as an example of such a pathological tissue image capturing system, a technology for dividing a pathological tissue image captured at a low magnification into small segments, calculating the proportions of tissue regions contained in the respective small segments, and giving priorities to the small segments in the descending order of the proportions of tissue regions thereby to give the pathologist a rough guide for determining a region of interest (ROI) in making a pathological tissue diagnosis.
However, the technology disclosed in JP-A No. 11-344676 suffers the following problems:
The first problem is that the proportion of a tissue region in a captured pathological tissue image is not directly indicative of the importance of the range.
For example, if a tissue exists in substantially the entire region of a pathological tissue slide, such as a breast cancer mammary gland operating material, then a captured pathological tissue image of the pathological tissue slide also contains a tissue almost in its entirety.
A cancer has its feature tending to appear in cell nuclei. Therefore, the importance of a range occupied by many cell nuclei is often high. If an entire pathological tissue image is occupied by a tissue, then the pathologist regards a region containing many cell nuclei as a ROI and observes the region at an enlarged scale.
However, even though the proportion of a tissue region in a pathological tissue image is high, if the region contains only fat or interstices, then the region is of low importance, and the pathologist does not pay much attention to the region in a pathological tissue diagnosis for a cancer.
According to the technology disclosed in JP-A No. 11-344676, a pathological tissue image is divided into small segments, and priorities are given to the small segments in the descending order of the proportions of tissue regions. However, as described above, a range in which the proportion of a tissue region is high may not necessarily be regarded as a ROI. Consequently, the priorities assigned to the small segments according to the technology disclosed in JP-A No. 11-344676 may not directly serves as priorities to be given by the pathologist in capturing ROI images at an enlarged scale.
It is therefore necessary to detect a ROI, such as a region containing many cell nuclei, which will be used by the pathologist in a pathological tissue diagnosis, from a pathological tissue image, rather than simply detecting a region in which the proportion of a tissue region is high.
The second problem is that according to the technology disclosed in JP-A No. 11-344676, an enlarged image capturing range which is of high importance and in which to capture an image at an enlarged scale cannot be selected unless the pathologist operates the pathological tissue image capturing system.
As described above with respect to the first problem, the priorities assigned to the small segments according to the technology disclosed in JP-A No. 11-344676 may not directly serves as priorities to be given by the pathologist in capturing ROI images at an enlarged scale. According to the technology disclosed in JP-A No. 11-344676, therefore, the pathologist is required to confirm a captured pathological tissue image on the display monitor and select an enlarged image capturing range while drawing on the priorities assigned by the pathological tissue image capturing system.
Furthermore, since an enlarged scale cannot be selected unless the pathologist operates the pathological tissue image capturing system according to the technology disclosed in JP-A No. 11-344676, the disclosed technology cannot be incorporated into an automatic pathological tissue diagnosis assisting system, which is a combination of the pathological tissue diagnosis assisting system disclosed in JP-A No. 2006-153742 and a pathological tissue image capturing system, for automatically carrying out an entire process from the capturing of a pathological tissue image to the diagnosis of the pathological tissue.
It is thus necessary to automatically detect a ROI from a pathological tissue image, select the detected ROI as an enlarged image capturing range, and capture an enlarged pathological tissue image representative of the selected enlarged image capturing range.
In order to solve the first problem and the second problem described above, therefore, a need arises for automatically detecting a ROI from a pathological tissue image, selecting the detected ROI as an enlarged image capturing range, and capturing an enlarged pathological tissue image representative of the selected enlarged image capturing range.